Data quality inspection method, device, equipment and medium

Abstract

The present disclosure relates to the technical field of map, in particular to a data quality inspection method and device, equipment and medium, the method comprises: acquiring the inspected mark-precision map data, and acquiring the mark-precision road data of the road corresponding to the preset road type from the inspected mark-precision map data;Acquire high-precision map data to be inspected, and based on the preset road type and the position data in the mark-precision road data, match the high-precision road data to be inspected from the high-precision map data to be inspected;Render the high-precision road data to be inspected and the material data used to make the high-precision road data to check the completeness and accuracy of the high-precision road data.The above-mentioned scheme enables the inspector to quickly and accurately inspect the data to be inspected in the high-precision map data, improves the inspection efficiency and improves the user experience.

Description

Technical Field

[0001] This disclosure relates to the field of map technology, specifically to a data quality inspection method, apparatus, equipment, and medium. Background Technology

[0002] With technological advancements, electronic maps are evolving from standard-precision maps to high-precision maps. High-precision maps, also known as high-resolution maps (HD maps), primarily serve applications such as intelligent driving and smart city management. Compared to standard-precision maps, high-precision maps provide not only road-level network data but also lane-level road network data.

[0003] Before high-precision map data is delivered for use, its quality needs to be checked to ensure that it meets the relevant requirements and to avoid problems with related functions or services implemented based on the high-precision map data due to unsatisfactory data quality.

[0004] In related technologies, the quality of high-precision map data still relies to some extent on manual inspection. The inventors of this disclosure have found that if the quality inspection platform can quickly and accurately locate the data to be inspected when relying on manual quality inspection, the quality inspection efficiency can be greatly improved. Summary of the Invention

[0005] To address the problems in the related technologies, embodiments of this disclosure provide a data quality inspection method, apparatus, device, and medium.

[0006] In a first aspect, this disclosure provides a data quality inspection method, which includes:

[0007] Obtain the quality-checked and refined map data, and from the quality-checked and refined map data, obtain the refined road data corresponding to the preset road types;

[0008] Acquire high-precision map data to be inspected, and based on the preset road types and location data in the high-precision road data, match the high-precision road data to be inspected from the high-precision map data to be inspected;

[0009] Render the high-precision road data to be inspected and the data used to create the high-precision road data, in order to check the completeness and accuracy of the high-precision road data.

[0010] In one implementation of this disclosure, the preset road type includes at least one of tunnels, toll stations, and road entrances / exits.

[0011] In one implementation of this disclosure, the method further includes:

[0012] Obtain the target quality inspection instructions;

[0013] From the already inspected and refined map data, obtain the refined road data corresponding to the preset road types, including:

[0014] In response to the target quality inspection command, retrieve the refined road data from the already inspected refined map data.

[0015] In one implementation of this disclosure, based on a preset road type and location data in the high-precision road data, the high-precision road data to be inspected is matched from the high-precision map data to be inspected, including:

[0016] Based on the preset road type, the target high-precision map data is obtained from the high-precision map data to be inspected. The target high-precision map data includes high-precision road data corresponding to the preset road type.

[0017] Based on the location data in the standard high-precision road data, the high-precision road data to be inspected is matched from the target high-precision map data.

[0018] In one implementation of this disclosure, the data includes image data and trajectory data. The image data includes photographs of the road corresponding to the high-precision road data to be inspected, and the trajectory data includes position information of multiple consecutive location points collected along the driving direction of the road corresponding to the high-precision road data to be inspected.

[0019] In one implementation of this disclosure, the data also includes road attribute information corresponding to the high-precision road data to be inspected.

[0020] In one implementation of this disclosure, the road attribute information includes at least one of the following: road grade, road surface type, road number, road name, map sheet number where the road is located, administrative division code where the road is located, number of lanes, and road length.

[0021] Secondly, this disclosure provides a data quality inspection device, wherein the device includes:

[0022] The precision data acquisition module is configured to acquire quality-checked precision map data and, from the quality-checked precision map data, acquire precision road data corresponding to the preset road types.

[0023] The high-precision data acquisition module is configured to acquire the high-precision map data to be inspected, and based on the preset road type and the location data in the standard road data, match the high-precision road data to be inspected from the high-precision map data to be inspected.

[0024] The data rendering module is configured to render the high-precision road data to be inspected and the data used to create the high-precision road data, so as to check the completeness and accuracy of the high-precision road data.

[0025] Thirdly, embodiments of this disclosure provide an electronic device including a memory and a processor, wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method as described in the first aspect and any implementation thereof.

[0026] Fourthly, this disclosure provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the method as described in the first aspect and any implementation thereof.

[0027] According to the technical solution provided in this disclosure, the following steps are performed: First, obtain the quality-inspected standard-precision map data and then obtain the standard-precision road data corresponding to a preset road type from the quality-inspected standard-precision map data. Second, obtain the high-precision map data to be inspected and, based on the preset road type and the location data in the standard-precision road data, match the high-precision road data to be inspected from the high-precision map data to be inspected. Third, render the high-precision road data to be inspected and the data used to create the high-precision road data to check the completeness and accuracy of the high-precision road data. Compared to high-precision map data, standard-precision map data has a smaller data volume, is updated faster, and has better completeness. Therefore, it is relatively easy to obtain high-accuracy and accurate standard-precision map data that has already been inspected. By obtaining standard-precision road data corresponding to preset road types from the inspected standard-precision map data, and matching the high-precision road data to be inspected from the high-precision map data based on the preset road types and location data in the standard-precision road data, the data to be inspected can be identified relatively quickly and accurately within the high-precision map data. By rendering the high-precision road data to be inspected and the data used to create the high-precision road data, the relevant inspectors can easily check the content in the rendered image corresponding to the high-precision road data to be inspected based on the image content in the rendered image that corresponds to the data used to create the high-precision road data. This allows them to determine whether the completeness and accuracy of the high-precision road data meet the requirements, thus enabling inspectors to quickly and accurately inspect the data to be inspected in the high-precision map data, improving inspection efficiency and enhancing user experience.

[0028] According to the technical solution provided in this disclosure, considering that tunnels, toll stations, or road entrances and exits do not appear frequently on roads, but rather appear at relatively long intervals, and that accidents involving vehicles passing through tunnels, toll stations, or road entrances and exits are likely to cause significant losses, by limiting the preset road types to include at least one of tunnels, toll stations, and road entrances and exits, the tunnels, toll stations, or road entrances and exits to be inspected can be quickly located in high-precision map data. This ensures that the high-precision road data matching the tunnels, toll stations, or road entrances and exits to be inspected in the high-precision map data has been checked, improving the reliability of the high-precision map data after quality inspection. Furthermore, compared with inspectors dragging the map to find the data corresponding to this type of road, this greatly improves the efficiency of quality inspection.

[0029] According to the technical solution provided in the embodiments of this disclosure, by obtaining the target quality inspection instruction and responding to the target quality inspection instruction, the target quality inspection instruction can be used to obtain the target quality road data from the already inspected target quality map data. This makes it easier for quality inspectors to control the initial data quality inspection and improves the user experience.

[0030] According to the technical solution provided in this disclosure, target high-precision map data is obtained from the high-precision map data to be inspected based on a preset road type. The target high-precision map data includes high-precision road data corresponding to the preset road type. Based on the location data in the high-precision road data, the high-precision road data to be inspected is matched from the target high-precision map data. This method can easily match the high-precision road data to be inspected and improves the matching efficiency.

[0031] According to the technical solution provided in this disclosure, by limiting the data to include image data and trajectory data, the difficulty for quality inspectors to check the completeness and accuracy of high-precision road data can be reduced, thereby improving the user experience.

[0032] According to the technical solution provided in this disclosure, by limiting the data to include road attribute information of the road corresponding to the high-precision road data to be inspected, it is possible for quality inspectors to gain a deeper understanding of the detailed information of the road corresponding to the high-precision road data to be inspected, which helps to improve the accuracy of quality inspection.

[0033] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0034] Other features, objects, and advantages of this disclosure will become more apparent from the following detailed description of non-limiting embodiments, taken in conjunction with the accompanying drawings. In the drawings:

[0035] Figure 1A schematic diagram of a tunnel region according to an embodiment of the present disclosure is shown.

[0036] Figure 2 A schematic diagram showing a road area where the number of lanes varies according to an embodiment of the present disclosure.

[0037] Figure 3 A flowchart illustrating a data quality inspection method according to an embodiment of the present disclosure is shown.

[0038] Figure 4 A schematic diagram showing a rendered image according to an embodiment of the present disclosure.

[0039] Figure 5 A structural block diagram of a data quality inspection apparatus according to an embodiment of the present disclosure is shown.

[0040] Figure 6 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0041] Figure 7 A schematic diagram of the structure of a computer system suitable for implementing the method according to embodiments of the present disclosure is shown. Detailed Implementation

[0042] In the following, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings to enable those skilled in the art to readily implement them. Furthermore, for clarity, portions unrelated to the description of exemplary embodiments have been omitted from the drawings.

[0043] In this disclosure, it should be understood that terms such as “comprising” or “having” are intended to indicate the presence of features, figures, steps, behaviors, components, parts or combinations thereof disclosed in this specification, and are not intended to exclude the possibility of the presence or addition of one or more other features, figures, steps, behaviors, components, parts or combinations thereof.

[0044] It should also be noted that, unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other. This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0045] In this disclosure, any operation involving the acquisition of user information or user data, or the display of user information or user data to others, is an operation authorized or confirmed by the user, or actively selected by the user.

[0046] With the development of electronic map technology, positioning services based on high-definition maps have gradually matured. High-definition maps, also known as high-resolution maps (HD maps), primarily serve applications such as intelligent driving and smart city management. Compared to traditional navigation maps, high-definition maps provide not only road-level navigation information but also lane-level navigation information. In recent years, intelligent driving technology based on high-definition maps has developed rapidly, leading to an increasing demand for these maps.

[0047] Before high-precision map data is delivered for use, its quality needs to be checked to ensure that it meets the relevant requirements and to avoid problems with related functions or services implemented based on the high-precision map data due to unsatisfactory data quality.

[0048] For example, the portion of high-precision map data corresponding to the tunnel area will be used as an example for illustration. Figure 1 A schematic diagram of a tunnel region according to an embodiment of the present disclosure is shown, such as Figure 1 As shown, if the data corresponding to the lane edge 102 at the tunnel entrance 101 is missing in the high-precision map data corresponding to tunnel 100, the vehicle may run out of the lane because it cannot recognize the lane edge 102 when it enters tunnel 100 through tunnel entrance 101, or it may collide with the tunnel wall of tunnel 100 because it cannot recognize the lane edge 102 when it exits tunnel 100 through tunnel entrance 101. This could lead to a traffic accident as the vehicle may collide with the tunnel wall at the tunnel entrance 101.

[0049] This explanation will take the section of high-precision map data corresponding to a road area where the number of lanes changes as an example. Figure 2 A schematic diagram showing a road area where the number of lanes changes according to an embodiment of the present disclosure is shown, such as... Figure 2As shown, the road area may include a first lane 201, a second lane 202, a third lane 203, a fourth lane 204, and a fifth lane 205 traveling in the same direction. The first lane 201 and the second lane 202 are both located upstream of the third lane 203, fourth lane 204, and fifth lane 205, meaning the number of lanes in the road area changes from two to three. If the data corresponding to the high-precision map data and the road area is missing, and the data for the connection between the first lane 201 or the second lane 202 and any of the third lane 203, fourth lane 204, or fifth lane 205 is missing, then when a vehicle is performing autonomous driving based on the high-precision map data, it may be unable to recognize the third lane 203, fourth lane 204, or fifth lane 205 when leaving the first lane 201 or the second lane 202, potentially causing the vehicle to veer off the lane and collide with objects outside the lane, resulting in a traffic accident.

[0050] To inspect high-precision map data, related technologies still rely to some extent on manual quality checks. However, when relying on manual quality checks, the data to be inspected in high-precision maps is often geographically dispersed. Inspectors must frequently drag the map to display the data to be checked on the screen, thus locating it for manual inspection, resulting in low efficiency. Therefore, the inventors of this disclosure have discovered that if a quality inspection platform can quickly and accurately locate the data to be inspected, it can significantly improve inspection efficiency.

[0051] The inventors of this disclosure propose a new solution: This solution involves acquiring high-precision map data that has already undergone quality inspection, and then acquiring high-precision road data corresponding to a preset road type from the high-precision map data that has already undergone quality inspection; acquiring high-precision map data to be inspected, and matching the high-precision road data to be inspected from the high-precision map data to be inspected based on the preset road type and the location data in the high-precision road data; and rendering the high-precision road data to be inspected and the data used to create the high-precision road data to check the completeness and accuracy of the high-precision road data. Compared to high-precision map data, standard-precision map data has a smaller data volume, is updated faster, and has better completeness. Therefore, it is relatively easy to obtain high-accuracy and accurate standard-precision map data that has already been inspected. By obtaining standard-precision road data corresponding to preset road types from the inspected standard-precision map data, and matching the high-precision road data to be inspected from the high-precision map data based on the preset road types and location data in the standard-precision road data, the data to be inspected can be identified relatively quickly and accurately within the high-precision map data. By rendering the high-precision road data to be inspected and the data used to create the high-precision road data, the relevant inspectors can easily check the content in the rendered image corresponding to the high-precision road data to be inspected based on the image content in the rendered image that corresponds to the data used to create the high-precision road data. This allows them to determine whether the completeness and accuracy of the high-precision road data meet the requirements, thus enabling inspectors to quickly and accurately inspect the data to be inspected in the high-precision map data, improving inspection efficiency and enhancing user experience.

[0052] Specifically, this disclosure proposes data quality inspection methods, devices, equipment, and media.

[0053] Figure 3 A flowchart illustrating a data quality inspection method according to an embodiment of this disclosure is shown. Figure 3 As shown, the data quality inspection method includes the following steps S301–S303:

[0054] In step S301, the quality-checked standard map data is obtained, and the standard road data corresponding to the preset road type is obtained from the quality-checked standard map data.

[0055] In step S302, the high-precision map data to be inspected is obtained, and based on the preset road type and the location data in the standard road data, the high-precision road data to be inspected is matched from the high-precision map data to be inspected.

[0056] In step S303, the high-precision road data to be inspected and the data used to create the high-precision road data are rendered to check the completeness and accuracy of the high-precision road data.

[0057] In one embodiment of this disclosure, high-precision map data can be understood as electronic maps created primarily for intelligent driving or smart city management, used for perception, positioning, and control. High-precision map data may include lane-level road information within a corresponding area, where lane-level road information can be understood as indicating the location data of the corresponding lane, the relative positional relationship between multiple lanes, and their connectivity. High-precision map data may also include road attribute information and points of interest (POIs), where road attribute information can be understood as including the road curvature, heading, slope, cross slope angle, road marking information, road boundary information, etc., of the corresponding road segment; point of interest information can be understood as indicating the latitude, longitude, and altitude of the point of interest, where a point of interest can be understood as a traffic sign, ground marking, light pole, traffic light, toll station, etc., described by a center point and multiple outer envelope points, or as a roadside curb, guardrail, tunnel, gantry, bridge, etc., described by a chain of continuous points.

[0058] Standard Definition Map (SD Map), also known as navigation electronic map or internet electronic map, includes the location data of roads within a corresponding area, road names, and corresponding points of interest. It should be noted that high-definition map data can have higher precision than standard definition map data.

[0059] It should be noted that, in order to facilitate matching in step S302, the area corresponding to the high-precision map data that has been inspected can be the same as the area corresponding to the high-precision map data to be inspected, or the area corresponding to the high-precision map data that has been inspected can include the area corresponding to the high-precision map data to be inspected.

[0060] For example, if the high-precision map data to be inspected corresponds to the Chaoyang District of Beijing, then the area corresponding to the standard-precision map data that has already been inspected can be the Chaoyang District of Beijing, or the area corresponding to the standard-precision map data that has already been inspected can be Beijing.

[0061] In one embodiment of this disclosure, road type can be understood as an attribute used to indicate the area through which the corresponding road passes. For example, the area through which the road passes may include bridges, service areas, gas stations, tunnels, and entrances and exits for entering and exiting closed roads (such as highways).

[0062] In one embodiment of this disclosure, the refined road data can be understood as the road data of the corresponding road in the refined map data, wherein the road data may include the location, elevation, etc. of multiple sampling points in the corresponding road.

[0063] In one embodiment of this disclosure, the location data in the refined road data can be understood as including the location information of at least one sampling point of the road corresponding to the refined road data, wherein the location information can be understood as coordinates in a geodetic coordinate system or coordinates obtained based on the Global Positioning System (GPS).

[0064] In one embodiment of this disclosure, the high-precision road data to be inspected can be understood as road data in the high-precision map data to be inspected where the road type belongs to a preset road type and the location data differs from the location data in the standard high-precision road data.

[0065] In one embodiment of this disclosure, high-precision road data to be inspected is matched from high-precision map data based on preset road types and location data in the standard road data. This can be understood as performing calculations by substituting preset road types, location data in the standard road data, and the high-precision map data to be inspected into a pre-set matching algorithm to obtain the high-precision road data to be inspected; or it can be understood as obtaining a pre-trained matching model, taking preset road types, location data in the standard road data, and the high-precision map data to be inspected as inputs to obtain the high-precision road data to be inspected output by the matching model.

[0066] In one embodiment of this disclosure, rendering the high-precision road data to be inspected and the data used to create the high-precision road data can be understood as rendering based on the high-precision road data to be inspected and the data used to create the high-precision road data to obtain a corresponding rendered image, which can then be displayed through a corresponding human-computer interaction device such as a display screen or touch screen. For example, the rendered image may include road image information corresponding to the high-precision road data to be inspected and text information from the data used to create the high-precision road data.

[0067] According to the technical solution provided in this disclosure, the following steps are performed: First, obtain the quality-inspected standard-precision map data and then obtain the standard-precision road data corresponding to a preset road type from the quality-inspected standard-precision map data. Second, obtain the high-precision map data to be inspected and, based on the preset road type and the location data in the standard-precision road data, match the high-precision road data to be inspected from the high-precision map data to be inspected. Third, render the high-precision road data to be inspected and the data used to create the high-precision road data to check the completeness and accuracy of the high-precision road data. Compared to high-precision map data, standard-precision map data has a smaller data volume, is updated faster, and has better completeness. Therefore, it is relatively easy to obtain high-accuracy and accurate standard-precision map data that has already been inspected. By obtaining standard-precision road data corresponding to preset road types from the inspected standard-precision map data, and matching the high-precision road data to be inspected from the high-precision map data based on the preset road types and location data in the standard-precision road data, the data to be inspected can be identified relatively quickly and accurately within the high-precision map data. By rendering the high-precision road data to be inspected and the data used to create the high-precision road data, the relevant inspectors can easily check the content in the rendered image corresponding to the high-precision road data to be inspected based on the image content in the rendered image that corresponds to the data used to create the high-precision road data. This allows them to determine whether the completeness and accuracy of the high-precision road data meet the requirements, thus enabling inspectors to quickly and accurately inspect the data to be inspected in the high-precision map data, improving inspection efficiency and enhancing user experience.

[0068] In one implementation of this disclosure, the preset road types include at least one of tunnels, toll stations, and road entrances / exits. Since tunnels, toll stations, or road entrances / exits do not appear frequently on roads, but rather occur at relatively long intervals, the tunnels, toll stations, or road entrances / exits to be inspected can be quickly located in high-precision map data using data of these road types in a high-precision map. This significantly improves quality inspection efficiency compared to inspectors dragging the map to find the corresponding data for these road types.

[0069] In one embodiment of this disclosure, a tunnel can be understood as including pedestrian tunnels, mountain tunnels, urban underground tunnels, river-crossing tunnels, undersea tunnels, etc. A toll station can be understood as a facility used to collect tolls from vehicles or pedestrians passing through a specific road. For example, a toll station may include a toll station that must be passed before entering or exiting a highway, tunnel, bridge, etc. Road entrances and exits can be understood as passages or roads (ramp, auxiliary road, connecting road, etc.) used for entering or exiting a specific road (e.g., highway, expressway, elevated road, bridge, etc.).

[0070] According to the technical solution provided in this disclosure, considering that tunnels, toll stations, or road entrances and exits do not appear frequently on roads, but rather appear at relatively long intervals, and that accidents involving vehicles passing through tunnels, toll stations, or road entrances and exits are likely to cause significant losses, by limiting the preset road types to include at least one of tunnels, toll stations, and road entrances and exits, the tunnels, toll stations, or road entrances and exits to be inspected can be quickly located in high-precision map data. This ensures that the high-precision road data matching the tunnels, toll stations, or road entrances and exits to be inspected in the high-precision map data has been checked, improving the reliability of the high-precision map data after quality inspection. Furthermore, compared with inspectors dragging the map to find the data corresponding to this type of road, this greatly improves the efficiency of quality inspection.

[0071] In one implementation of this disclosure, the method further includes:

[0072] Obtain the target quality inspection instructions;

[0073] From the already inspected and refined map data, obtain the refined road data corresponding to the preset road types, including:

[0074] In response to the target quality inspection command, retrieve the refined road data from the already inspected refined map data.

[0075] In one embodiment of this disclosure, obtaining a target quality inspection instruction can be understood as receiving a target quality inspection instruction sent by other devices or systems, or as obtaining a target quality inspection instruction input through a human-computer interaction device such as a keyboard, mouse, touch screen, microphone, etc.

[0076] According to the technical solution provided in the embodiments of this disclosure, by obtaining the target quality inspection instruction and responding to the target quality inspection instruction, the target quality inspection instruction can be used to obtain the target quality road data from the already inspected target quality map data. This makes it easier for quality inspectors to control the initial data quality inspection and improves the user experience.

[0077] In one implementation of this disclosure, based on a preset road type and location data in the high-precision road data, the high-precision road data to be inspected is matched from the high-precision map data to be inspected, including:

[0078] Based on the preset road type, the target high-precision map data is obtained from the high-precision map data to be inspected. The target high-precision map data includes high-precision road data corresponding to the preset road type.

[0079] Based on the location data in the standard high-precision road data, the high-precision road data to be inspected is matched from the target high-precision map data.

[0080] In one embodiment of this disclosure, target high-precision map data is obtained from the high-precision map data to be inspected based on a preset road type. This can be understood as sequentially matching the road type of each road in the high-precision map data to be inspected according to the preset road type, and determining the high-precision road data corresponding to the preset road type based on the matching results, thereby determining the target high-precision map data where the high-precision road data corresponding to the preset road type is located; or it can be understood as querying the high-precision map data to be inspected according to the preset road type, and determining the high-precision road data corresponding to the preset road type based on the query results, thereby determining the target high-precision map data where the high-precision road data corresponding to the preset road type is located.

[0081] In one embodiment of this disclosure, high-precision road data to be inspected is matched from the target high-precision map data based on the location data in the standard-precision road data. This can be understood as sequentially matching the location data in the high-precision road data of each road in the target high-precision map data with the location data in the standard-precision road data, and determining the high-precision road data to be inspected based on the matching results. That is, the road data corresponding to the road in the target high-precision map data whose location data does not match the location data in the standard-precision road data is the high-precision road data to be inspected. Alternatively, it can be understood as querying the target high-precision map data based on the location data in the standard-precision road data, and determining the road data corresponding to the road in the target high-precision map data whose location data does not match the location data in the standard-precision road data based on the query results.

[0082] According to the technical solution provided in this disclosure, target high-precision map data is obtained from the high-precision map data to be inspected based on a preset road type. The target high-precision map data includes high-precision road data corresponding to the preset road type. Based on the location data in the high-precision road data, the high-precision road data to be inspected is matched from the target high-precision map data. This method can easily match the high-precision road data to be inspected and improves the matching efficiency.

[0083] In one implementation of this disclosure, the data includes image data and trajectory data. The image data includes photographs of the road corresponding to the high-precision road data to be inspected, and the trajectory data includes position information of multiple consecutive location points collected along the driving direction of the road corresponding to the high-precision road data to be inspected.

[0084] In one embodiment of this disclosure, the photograph of the road corresponding to the high-precision road data to be inspected can be understood as a photograph taken by an image acquisition party, such as an image acquisition vehicle, traveling on the road corresponding to the high-precision road data to be inspected, or as an image of the road corresponding to the high-precision road data to be inspected taken by other image acquisition parties, such as drones, satellites, etc.

[0085] In one embodiment of this disclosure, the location information of multiple consecutive locations collected along the driving direction of the road corresponding to the high-precision road data to be inspected can be understood as the location information collected at multiple consecutive locations by a vehicle carrying a location information collection device (such as a global positioning system information collection device) while driving along the driving direction of the road corresponding to the high-precision road data to be inspected.

[0086] In one embodiment of this disclosure, a photograph of the road corresponding to the high-precision road data to be inspected can be rendered simultaneously with the high-precision road data in a single image frame, allowing quality inspectors to check the high-precision road data based on the photograph. Based on the position information of multiple consecutive points collected along the driving direction of the road corresponding to the high-precision road data to be inspected, the corresponding position information can be rendered as the vehicle's driving trajectory in the rendered image. Furthermore, based on the high-precision road data to be inspected, the corresponding road trajectory can be rendered in the same rendered image, facilitating quality inspectors to check the high-precision road data by comparing the driving trajectory and the road trajectory in the rendered image.

[0087] For example, Figure 4 A schematic diagram showing a rendered image according to an embodiment of the present disclosure. (e.g.) Figure 4 As shown, the rendered image 400 may include a photo 401 of the road corresponding to the high-precision road data to be inspected, a vehicle trajectory 402 for location information collection, and a road trajectory 403. The vehicle trajectory 402 for location information collection is rendered based on the location information of multiple consecutive location points collected along the driving direction of the road corresponding to the high-precision road data to be inspected, and the road trajectory 403 is rendered based on the high-precision road data to be inspected.

[0088] According to the technical solution provided in this disclosure, by limiting the data to include image data and trajectory data, the difficulty for quality inspectors to check the completeness and accuracy of high-precision road data can be reduced, thereby improving the user experience.

[0089] In one implementation of this disclosure, the data also includes road attribute information corresponding to the high-precision road data to be inspected.

[0090] In one embodiment of this disclosure, road attribute information can be understood as information used to identify the function and identity of a road.

[0091] For example, road attribute information may include at least one of the following: road grade, road surface type, road number, road name, map sheet number where the road is located, administrative division code where the road is located, number of lanes, and road length.

[0092] According to the technical solution provided in this disclosure, by limiting the data to include road attribute information of the road corresponding to the high-precision road data to be inspected, it is possible for quality inspectors to gain a deeper understanding of the detailed information of the road corresponding to the high-precision road data to be inspected, which helps to improve the accuracy of quality inspection.

[0093] Figure 5 A structural block diagram of a data quality inspection apparatus according to an embodiment of the present disclosure is shown. This apparatus can be implemented as part or all of an electronic device through software, hardware, or a combination of both.

[0094] like Figure 5 As shown, the data quality inspection device 500 includes:

[0095] The precision data acquisition module 501 is configured to acquire the quality-inspected precision map data and acquire precision road data corresponding to the preset road type from the quality-inspected precision map data;

[0096] The high-precision data acquisition module 502 is configured to acquire the high-precision map data to be inspected, and based on the preset road type and the location data in the standard road data, match the high-precision road data to be inspected from the high-precision map data to be inspected;

[0097] The data rendering module 503 is configured to render the high-precision road data to be inspected and the data used to create the high-precision road data, so as to check the completeness and accuracy of the high-precision road data.

[0098] According to the technical solution provided in this disclosure, the following steps are performed: First, obtain the quality-inspected standard-precision map data and then obtain the standard-precision road data corresponding to a preset road type from the quality-inspected standard-precision map data. Second, obtain the high-precision map data to be inspected and, based on the preset road type and the location data in the standard-precision road data, match the high-precision road data to be inspected from the high-precision map data to be inspected. Third, render the high-precision road data to be inspected and the data used to create the high-precision road data to check the completeness and accuracy of the high-precision road data. Compared to high-precision map data, standard-precision map data has a smaller data volume, is updated faster, and has better completeness. Therefore, it is relatively easy to obtain high-accuracy and accurate standard-precision map data that has already been inspected. By obtaining standard-precision road data corresponding to preset road types from the inspected standard-precision map data, and matching the high-precision road data to be inspected from the high-precision map data based on the preset road types and location data in the standard-precision road data, the data to be inspected can be identified relatively quickly and accurately within the high-precision map data. By rendering the high-precision road data to be inspected and the data used to create the high-precision road data, the relevant inspectors can easily check the content in the rendered image corresponding to the high-precision road data to be inspected based on the image content in the rendered image that corresponds to the data used to create the high-precision road data. This allows them to determine whether the completeness and accuracy of the high-precision road data meet the requirements, thus enabling inspectors to quickly and accurately inspect the data to be inspected in the high-precision map data, improving inspection efficiency and enhancing user experience.

[0099] This disclosure also discloses an electronic device, Figure 6 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0100] like Figure 6 As shown, the electronic device includes a memory and a processor, wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method according to embodiments of the present disclosure.

[0101] This disclosure provides a data quality inspection method, including:

[0102] Obtain the quality-checked and refined map data, and from the quality-checked and refined map data, obtain the refined road data corresponding to the preset road types;

[0103] Acquire high-precision map data to be inspected, and based on the preset road types and location data in the high-precision road data, match the high-precision road data to be inspected from the high-precision map data to be inspected;

[0104] Render the high-precision road data to be inspected and the data used to create the high-precision road data, in order to check the completeness and accuracy of the high-precision road data.

[0105] In one implementation of this disclosure, the preset road type includes at least one of tunnels, toll stations, and road entrances / exits.

[0106] In one implementation of this disclosure, the method further includes:

[0107] Obtain the target quality inspection instructions;

[0108] From the already inspected and refined map data, obtain the refined road data corresponding to the preset road types, including:

[0109] In response to the target quality inspection command, retrieve the refined road data from the already inspected refined map data.

[0110] In one implementation of this disclosure, based on a preset road type and location data in the high-precision road data, the high-precision road data to be inspected is matched from the high-precision map data to be inspected, including:

[0111] Based on the preset road type, the target high-precision map data is obtained from the high-precision map data to be inspected. The target high-precision map data includes high-precision road data corresponding to the preset road type.

[0112] Based on the location data in the standard high-precision road data, the high-precision road data to be inspected is matched from the target high-precision map data.

[0113] In one implementation of this disclosure, the data includes image data and trajectory data. The image data includes photographs of the road corresponding to the high-precision road data to be inspected, and the trajectory data includes position information of multiple consecutive location points collected along the driving direction of the road corresponding to the high-precision road data to be inspected.

[0114] In one implementation of this disclosure, the data also includes road attribute information corresponding to the high-precision road data to be inspected.

[0115] In one implementation of this disclosure, the road attribute information includes at least one of the following: road grade, road surface type, road number, road name, map sheet number where the road is located, administrative division code where the road is located, number of lanes, and road length.

[0116] Figure 7 A schematic diagram of the structure of a computer system suitable for implementing the method according to embodiments of the present disclosure is shown.

[0117] like Figure 7As shown, the computer system includes a processing unit that can execute various methods described above based on a program stored in a read-only memory (ROM) or a program loaded from a storage portion into a random access memory (RAM). The RAM also stores various programs and data required for the operation of the computer system. The processing unit, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0118] The following components are connected to the I / O interface: input sections including keyboards, mice, etc.; output sections including cathode ray tubes (CRTs), liquid crystal displays (LCDs), and speakers; storage sections including hard disks, etc.; and communication sections including network interface cards such as LAN cards and modems. The communication section performs communication processes via a network such as the Internet. Drives are also connected to the I / O interface as needed. Removable media, such as disks, optical disks, magneto-optical disks, semiconductor memories, etc., are installed on the drive as needed so that computer programs read from them can be installed into the storage section as needed. The processing unit can be implemented as a CPU, GPU, TPU, FPGA, NPU, etc.

[0119] In particular, according to embodiments of this disclosure, the methods described above can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program containing program code for performing the methods described above. In such embodiments, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium.

[0120] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0121] The units or modules described in the embodiments of this disclosure can be implemented in software or programmable hardware. The described units or modules can also be located in a processor, and the names of these units or modules do not necessarily constitute a limitation on the unit or module itself.

[0122] In another aspect, this disclosure also provides a computer-readable storage medium, which may be a computer-readable storage medium included in the electronic device or computer system described above; or it may be a standalone computer-readable storage medium not assembled into a device. The computer-readable storage medium stores one or more programs, which are used by one or more processors to perform the methods described in this disclosure.

[0123] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

Claims

1. A data quality inspection method, wherein, include: Obtain the quality-checked and refined map data, and from the quality-checked and refined map data, obtain the refined road data corresponding to the preset road type; Acquire high-precision map data to be inspected, and based on the preset road type and the location data in the high-precision road data, match the high-precision road data to be inspected from the high-precision map data to be inspected, wherein the road type is used to indicate the attributes of the area traversed by the corresponding road; The high-precision road data to be inspected and the data used to create the high-precision road data are rendered to check the completeness and accuracy of the high-precision road data.

2. The method of claim 1, wherein, The preset road types include at least one of tunnels, toll stations, and road entrances / exits.

3. The method of claim 1, wherein, The method further includes: Obtain the target quality inspection instructions; The step of obtaining refined road data corresponding to preset road types from the already inspected refined map data includes: In response to the target quality inspection instruction, the refined road data is obtained from the inspected refined map data.

4. The method of any of claims 1-3, wherein, The process of matching high-precision road data to be inspected from the high-precision map data based on the preset road type and the location data in the high-precision road data includes: Based on the preset road type, target high-precision map data is obtained from the high-precision map data to be inspected, and the target high-precision map data includes high-precision road data corresponding to the preset road type; Based on the location data in the standard high-precision road data, the high-precision road data to be inspected is matched from the target high-precision map data.

5. The method of any one of claims 1-3, wherein, The data includes image data and trajectory data. The image data includes photographs of the roads corresponding to the high-precision road data to be inspected, and the trajectory data includes location information of multiple consecutive points collected along the driving direction of the roads corresponding to the high-precision road data to be inspected.

6. The method of any one of claims 1-3, wherein, The data also includes road attribute information of the roads corresponding to the high-precision road data to be inspected.

7. The method of claim 6, wherein, The road attribute information includes at least one of the following: road grade, road surface type, road number, road name, map sheet number where the road is located, administrative division code where the road is located, number of lanes, and road length.

8. A data quality inspection apparatus, wherein, The device includes: The precision data acquisition module is configured to acquire quality-inspected precision map data, and from the quality-inspected precision map data, acquire precision road data corresponding to the preset road type; The high-precision data acquisition module is configured to acquire high-precision map data to be inspected, and based on the preset road type and the location data in the high-precision road data, match the high-precision road data to be inspected from the high-precision map data to be inspected, wherein the road type is used to indicate the attributes of the area traversed by the corresponding road; The data rendering module is configured to render the high-precision road data to be inspected and the data used to create the high-precision road data, so as to check the completeness and accuracy of the high-precision road data.

9. An electronic device, comprising: The method includes a memory and a processor; wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method steps of any one of claims 1-7.

10. A computer readable storage medium having stored thereon computer instructions, wherein, When executed by a processor, the computer instructions implement the method steps of any one of claims 1-7.

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